Motivated by the complex control issues raised by COVID-19, this article investigates the optimal control of an epidemic of a Susceptible-Infective-Removed-Susceptible (SIRS) infection when two main instruments – social distancing and vaccination – are available to the social planner. The resulting two-control optimal problem is set within a parsimonious economic model in which the planner minimizes an objective function that weights epidemiological and economic costs by choosing the extent of social distancing in a first stage of the epidemic and both social distancing and the tax rate to finance vaccination during a subsequent stage. The article shows (i) how to combine the two policy tools depending on the planner’s degree of rationality; (ii) the importance of the planner’s expectation on the date of vaccine arrival, and how the expected efficacy of the vaccine can affect the optimal social distancing trajectory in the pre-vaccination period, and (iii) the use of social distancing as the only instrument to optimally control the epidemic when the vaccine supply is rationed.
This theoretical work reconsiders the classification of competition in economic theory through a transdisciplinary framework grounded in complexity science, biological and ecological sciences, and evolutionary economics. We conceptualize economic ecosystems as real complex adaptive systems (CAS), structurally embedded within broader social and biological domains. Within this framework, competition is classified as a non-beneficial (–/–) interaction. The article then examines the systemic proposition that, when competitive relationships become dominant, intense, or exclusionary, they may undermine long-term systemic resilience by disrupting interdependence, reducing diversity, and accelerating resource depletion. Based on a transdisciplinary, critical, and integrative literature review of 198 sources, we construct a typology of beneficial and non-beneficial interactions and introduce a theoretical formula to evaluate systemic equilibrium in economic systems. While the model is conceptual by design, it provides a foundation for future empirical testing via network analysis and agent-based modeling. Grounded in panarchy theory, the article frames economic systems as structurally interlinked with higher-order ecological and social dynamics. We conclude that, within a CAS-based and panarchically embedded view of economic systems, maintaining the normative centrality of competition as inherently beneficial is theoretically inconsistent with its classification as a non-beneficial interaction, even when competitive processes may coincide with perceived short-term gains, localized efficiencies, or innovation outcomes.
Using country-sector data for 24 European countries from 2008 to 2019, we examine how economic complexity shapes firm dynamics. We study whether more complex productive structures foster entrepreneurship or instead act as a barrier to market entry, focusing on firm entry, exit, churn, and survival across size classes. To address endogeneity, we implement an instrumental variables strategy based on regional leave-one-out averages of the Economic Complexity Index (ECI). Our results suggest that higher economic complexity significantly reduces firm entry and business churn, and lowers medium- and long-term survival, particularly for larger firms. For microenterprises, the negative effects on longer-term survival are weaker, despite a stronger negative effect at entry. These findings suggest that economic complexity operates less as a broadly enabling entrepreneurial environment and more as a selective filter, with heterogeneous effects across firm sizes.
Western political economy has long interpreted government–business relations in China through the lens of rent-seeking theory, as an interpretive framework that reduces complex state–market interactions to a simple predator–prey logic of bureaucratic extraction. This paper argues that the rent-seeking paradigm constitutes a systematic theoretical misdiagnosis: it imports assumptions about homo economicus, competitive market equilibrium, and institutional performance criteria that are institutionally parochial and empirically inadequate for understanding China’s development trajectory. This paper develops an alternative framework—symbiotic co-evolutionary political economy (SCPE)—grounded in evolutionary economics, complexity theory, and Chinese institutional history. SCPE rests on three interrelated theoretical contributions. First, this paper replaces the atomistic self-interested homo economicus with a social-relational economic agent: an agent whose preferences, strategies, and performance are constitutively shaped by social position, relational obligation, and collective identity. Second, this paper reconceptualizes competition itself, distinguishing predatory zero-sum competition from what this paper terms developmental symbiotic competition (DSC): a form of competitive co-evolution in which state and business actors simultaneously compete for resources and cooperate to expand the productive frontier, generating positive-sum dynamics that rent-seeking theory cannot accommodate. Third, this paper proposes an evolutionary institutional performance standard that evaluates institutional arrangements not by their conformity to an ideal-type market equilibrium but by their adaptive fitness—their capacity to sustain developmental trajectories under uncertainty, absorb distributional shocks, and generate productive co-evolutionary dynamics over time. The SCPE framework generates predictions that contradict the rent-seeking paradigm but are consistent with China’s development record, and opens new theoretical space for a genuinely comparative political economy of state–business relations.
This paper aims to investigate how lagging regions can achieve knowledge-driven, endogenous economic growth through doing-using-interacting (DUI)-driven innovation activities. While traditional theories of endogenous growth emphasize the importance of codified, R D-based knowledge (STI mode of innovation), they largely neglect the innovative capacities of SMEs in lagging regions that are primarily reliant on tacit knowledge. Recent research has highlighted the importance of synthetic knowledge and informal innovation processes in such settings, but solid empirical evidence of their regional embeddedness remains scarce. Our study addresses this gap by qualitatively examining 63 SMEs across ten lagging German regions, focusing on how regional contextual factors shape three types of DUI learning: learning-by-doing, learning-by-using, and learning-by-interacting. The empirical findings reveal three central insights. First, internal learning processes are present across all ten study regions, yet their form and effectiveness are highly dependent on local vocational training structures, business culture, and the availability of skilled labor. Second, external learning via cooperation with regional partners only has lasting innovation effects when local institutions and trust-based networks support it. Third, learning-by-using is contingent on regional infrastructure and customer proximity, highlighting the significant spatial disparities in innovation capacity across lagging regions. Our results show that DUI innovations are not only viable in lagging regions; they can also serve as key drivers of regional economic growth, so long as regional characteristics are adequately considered. Ultimately, the study proposes a typology of lagging regions based on their DUI learning environments and calls for a shift in regional innovation policy towards support for informal, decentralized innovation practices. Future research may test this typology quantitatively and explore the findings’ transferability across different national contexts.
The management of infectious diseases increasingly relies on innovative but costly pharmaceutical treatments, raising complex trade-offs between epidemiological containment, fiscal sustainability, and institutional coordination. We develop a spatially structured agent-based model in which decentralized health authorities allocate treatment under local budget constraints while infection spreads across a two-dimensional lattice through neighborhood spillovers. Within each location, treatment intensity is chosen endogenously, interacting with local GDP dynamics and pricing conditions. Simulation results reveal that purely decentralized optimization mitigates but does not reverse infection growth within policy-relevant horizons, generating persistent spatial heterogeneity in both epidemiological and economic outcomes. We then introduce bounded spatial policy interaction, showing that partial coordination substantially improves containment but may increase the persistence of fiscal engagement. Extending the model to heterogeneous and time-varying pricing, we find that price discrimination amplifies medium-run infection and fiscal pressure under decentralization. However, when surplus revenues finance endogenous R D, treatment efficacy improves over time, generating a feedback mechanism in which innovation mitigates long-run epidemiological and economic losses. Our findings highlight the critical interplay between spatial structure, decentralized decision-making, pricing design, and innovation incentives in shaping epidemic outcomes. Effective management of high-cost treatments requires not only medical efficacy but also institutional coordination and carefully designed market mechanisms.
In industrial development, the relationship between corporate growth and company size is essential because it influences convergence behavior and market concentration in a market. One important theory on this relationship is Gibrat’s law claiming that corporate growth is independent of company size. This study examines Gibrat’s law using an unbalanced panel covering European electricity generators from 2012 to 2020. The European electricity generation sector is interesting due to past liberalization and market integration, as well as capital-intensive production processes. Gibrat’s law is explored using σ -convergence, and unconditional and conditional β -convergence. A battery of different measures for company size is employed. Moreover, the relationship between company size and the variance of growth processes is examined. Overall, European electricity generators converge in company size, rejecting Gibrat’s law. Additionally, the variance of growth processes is driven by firm size. Last, state ownership and renewable subsidies drive firm-level convergence speeds.
Modern organizations are encountering significant challenges due to a combination of rapid technological changes, increasing sociocultural complexity, and dispersed, diverse workforces. The ability of businesses and organizations to adapt constructively to these concurrent trends is being strained by crucial shifts in their employees' perceptions of their roles and value within the enterprise. Examining the problem-solving and organizational creativity of natural biological systems and applying lessons learned from the collective behaviors of our constituent cells offers valuable insights into how to build a flexible, resilient, and responsive management architecture that can encourage a coherent, productive organizational culture. Our cellular intelligence model proposes a biomimetic framework for organizational management inspired by empirical cellular behavioral patterns and theoretically grounded in the informational realism paradigm and mindset agency theory. Drawing upon cellular behavior patterns and metacybernetic recursive informational theory, twelve guiding principles are outlined for adaptive, coherent, and resilient organizational design and management. This approach offers a novel, post-hierarchical, decentralized model that prioritizes interdependence, fluid communication, and multi-level reciprocity, supporting collective and autonomous decision-making and problem-solving to enable flexible organizational adaptation and promote continuous, sustainable growth.
Uncovered interest parity (UIP) is routinely rejected at short horizons, motivating departures toward heterogeneous-expectations frameworks. We estimate a behavioral UIP (BUIP) law of motion for monthly exchange-rate returns, where expectations form as a profitability-weighted average of a chartist (trend-following) rule and a fundamentalist rule anchored to absolute purchasing power parity (PPP). Building on Proaño (2011, 2013), rule shares evolve through a discrete-choice mechanism. We compare the structural BUIP against a reduced-form logistic smooth-transition regression across fourteen bilateral USD exchange rates (seven advanced, seven emerging) from the early 1980s to 2025. We reject linearity for 13 of 14 currencies, with nonlinear models reducing in-sample fit. However, the Akaike information criterion frequently prefers the linear benchmark in advanced economies, suggesting nonlinearity is most rewarded in emerging markets. The structural BUIP identifies stabilizing PPP-consistent mean reversion in seven countries. While embedding heterogeneous beliefs into UIP partly reconciles the parity condition with nonlinear dynamics, the mixed evidence on PPP correction highlights the limitations of a “one-model-fits-all” approach. Ultimately, the choice of fundamental anchor appears to be highly market- and time-dependent.
This paper examines whether the duration of informality before legal registration increases the risk of post-formalization zombification among firms in Sub-Saharan Africa. While the zombie-firm literature has largely explained persistent firm stagnation through financial forbearance and credit misallocation, this paper develops an alternative explanation based on informality, organizational imprinting, and delayed capability accumulation. Using firm-level data from the World Bank Enterprise Surveys covering 44 Sub-Saharan African countries over the period 2009–2024, we construct an ordered zombification score capturing persistent stagnation in growth, productivity, innovation, and investment behavior. The empirical analysis relies on a recursive Conditional Mixed Process framework that accounts for the endogeneity of informality duration and selection into informal entry. The results show that longer informal spells before registration shift firms away from lower zombification categories and toward more severe post-formalization stagnation. This pattern appears in both manufacturing and services and is robust to alternative binary measures, inverse propensity weighting, and fractional response models with control-function correction. Further heterogeneity analyses show that the relationship holds across country-income groups and is especially evident among low- to medium–low-technology manufacturing industries. The findings suggest that formalization alone may not erase the organizational legacy of prolonged informality.
This paper studies business innovation in China, a country that has become an economic power in recent years. The literature on innovation in “business innovation modes” has come to the forefront for its capacity to identify archetypical sets of business practices (bundles of internal and external drivers) that firms adopt to stimulate innovation. This is a strand that moves away from the analysis of the impact of individual factors (e.g., R D, human capital) and instead identifies the impact of bundles of resources, capabilities and practices that firms and their entrepreneurs/teams apply to attain their competitiveness objectives. Specifically, these are the STI (science and technology-based innovation) and DUI mode (innovation based on learning-by-doing, by-using, and by-interacting) or a combination of the two. Therefore, it is very important from a practical perspective as it provides a reliable framework where businesses can learn from relevant empirical findings and benefit from implementing appropriate policy measures. Based on panel data from Chinese provinces 2016–2023, we first analyze how firms use these innovation modes to impact technological and non-technological innovation. These modes are effective; however, they focus on the technological side (product innovation). A further contribution of this study is the inclusion of social capital as a moderating factor for innovation, particularly for the DUI innovation mode, which relies on effective interaction across personnel and the supply chain. We find a significant impact of bonding social capital for process innovation when using the DUI mode.
Although national innovation systems (NIS) have been studied for more than thirty years in both developed and developing countries, doing-using-interacting (DUI) policies remain largely absent from the innovation agendas of developing economies. The literature on NIS is not new, and it has already incorporated the DUI mode into the framework of the learning economy. Yet, existing research on DUI has offered little guidance for national-scale innovation policy in developing countries, as DUI has been analyzed primarily at the micro and mesoeconomic levels. Consequently, recent studies have concentrated on firm-level performance and the role of STI and/or DUI modes within regional innovation systems in advanced economies. Our conceptual contribution revisits the NIS literature and scales up the DUI mode by adopting an institutional and macroeconomic perspective tailored to developing contexts. On this basis, we identify three types of DUI policies, ranging from the least to the most transformative at the societal level: (i) a basic policy linking education, training and labor markets to create learning opportunities; (ii) an intermediate policy fostering collaboration between formal and informal actors through interactive learning spaces; and (iii) an inclusive, transformative policy embedding the DUI mode within a societal learning culture.
We analyze the role of social interactions in driving the effectiveness of social distancing to mitigate the economic consequences of infectious diseases. Individuals choose whether to comply with social distancing measures by accounting for health and social considerations, determining the dynamic evolution of disease prevalence. We show that the feedback effects between health and social conditions imply that the economy may converge to a disease-free or endemic situation, giving rise to a variety of alternative scenarios, in which unique or multiple stable equilibria exist, monotonic or non-monotonic trajectories occur, cyclical behavior or path-dependency arise. Moreover, by extending the analysis to a stochastic setup to account for the role of uncertainty, we show that the predictions of a deterministic analysis may not be enough to perform robust policy analysis, as the stochastic outcome may largely differ from the deterministic one.
Since the arrival of mobile technologies, analyses of the competitive landscape between fixed and mobile services have been a focal point for scholars, policymakers, and regulators. To examine the dynamics between mobile and fixed services we have applied Lotka–Volterra, or predator–prey models, analyzing various access and application-related variables to understand their interplay. Our findings generally support the dominance of mobile networks; however, the impact of substitution varies between voice and data services and is powerfully influenced by the technological innovations and the resulting shifts in customers’ demand and perception. Two historical game-changers profoundly shaped the evolution of communication services over the past three decades: The “personal” character of mobile services (as opposed to the “local” character of fixed) and the advent of broadband applications. Our investigation sheds light on how these developments have redefined the concept of communication services, the evolution of communication markets, and the primary infrastructures that support them.
This paper studies how informality reshapes real–financial feedback and the emergence of endogenous macroeconomic instability in developing economies. We develop a parsimonious nonlinear model that combines (i) an underwriting-based liquidity–solvency mechanism in which funding conditions in the financially integrated segment depend on discounted expectations of liquidity, and (ii) a demand-driven real block with bounded output adjustment in a dual economy where informal activity is more cash-flow based and has lower short-run adjustment capacity. In the baseline map, effective formality governs a trade-off: greater financial integration and productive capacity raise average activity, but also strengthen belief-sensitive financing conditions and move the economy closer to instability. Local analysis characterizes Flip (period-doubling) and Neimark–Sacker bifurcation routes. We then endogenize belief composition and effective formal participation via performance-based (logit) updating interpreted as cyclical variation in reliance on formal instruments. Stochastic simulations and Monte Carlo sensitivity analysis show that volatility is driven mainly by the intensity of cyclical reallocation between formal and informal margins.
We develop an evolutionary model to study the emergence of natural property rights (NPR) in a structured population with an endogenously evolving connection network. We propose a novel network-rewiring rule that governs how agents adjust their social connections. The rule is compatible with economic rationality and generates a mechanism of selfish punishment that stabilizes an equilibrium in which property rights are respected. Crucially, this punishment does not rely on third-party enforcement, altruistic behavior, or exogenous asymmetries between owners and intruders, and can therefore arise spontaneously among selfish agents. We compare our network-based model with the canonical endowment-effect model and show that their distinct driving forces generate fundamentally different convergence paths toward NPR and opposite welfare dynamics. While the endowment-effect model relies on defensive fighting to sustain convergence, our model allows NPR to emerge peacefully through endogenous partner selection. Along this process, individual incentives are aligned with aggregate population welfare. From this perspective, our framework offers a novel and historically plausible explanation for the emergence of natural property rights.
The financial instability hypothesis of the heterodox economist H.P. Minsky came to the fore as a result of the international financial crisis triggered by the sub-prime mortgage crisis in the U.S. Many post-Keynesian economists have developed Minsky’s arguments into mathematical models that depict two types of Minskyian financial structures, which we identify as the lenders’ risk type (LR) and the hedge, speculative, and Ponzi type (HSP). We examine the effects of monetary and fiscal policy in macrodynamic models that consider both the LR and HSP financial structures and demonstrate that the effects depend on the significance of those structures. We emphasize the significance of stable financial structures and the mix of monetary and fiscal policies needed to stabilize the economy. However, we show that the policy mix cannot completely eliminate the fragility of the HSP financial structure. It is crucial to establish institutional frameworks that mitigate the HSP financial structure’s fragility.
The existing literature has not reached a consensus on the relationship and mechanisms between innovation and income inequality, particularly in the context of urban–rural disparities. To address this issue, we investigate the conditions under which innovation increases or decreases income inequality. We propose that the impact of innovation on income inequality varies across different stages of innovation development. Using provincial-level panel data from China spanning 2009 to 2020, we constructed multiple indicators to measure innovation and found that the impact of innovation on urban–rural income inequality exhibits an inverted U-shaped trend: innovation initially exacerbates urban–rural income inequality and subsequently alleviates it. This phenomenon is influenced by mechanisms such as the learning-by-doing effect, the erosion effect, and industrial structure upgrading. Additionally, our research shows that regional differences in the intensity of these mechanisms account for the heterogeneity in the impact of innovation on income inequality. This study contributes to a deeper understanding of the dual effects of innovation on socio-economic disparities.
This paper presents a demand-led growth model augmented with induced technical change to address the two Harrod’s problems in growth theory. Building on recent developments in the supermultiplier literature, we investigate how both Harrodian instability problems can be resolved through two complementary mechanisms: (1) autonomous, non-capacity-creating demand components growing at an exogenous rate, and (2) endogenous technical change responsive to income distribution. On the one hand, demand shocks are absorbed via adjustments in the investment share, allowing capital accumulation to align with the exogenously determined growth rate of autonomous expenditures. On the other hand, labor market imbalances trigger productivity adjustments that reconcile natural and warranted growth by altering the wage share. This dual adjustment mechanism allows the system to sustain normal capacity utilization and stable employment rates, while preserving demand-led growth outcomes.
